{"resourceId":"usbe-utah-r277-334-draft-classroom-technology-ai-rule-20261005","versions":[{"version":"external-1141f135455bdf42a20cc23af1c6d98ac652b9bf54d33fa0d42d35249af9c563","resource":{"id":"usbe-utah-r277-334-draft-classroom-technology-ai-rule-20261005","title":"Utah State Board of Education draft rule R277-334 (Draft 1, 5 Oct 2026): districts must keep approved AI tool inventories, bar student generative AI unless an educator authorises it, notify parents and certify compliance","organization":"Utah State Board of Education (USBE)","sector":"State K-12 rulemaking on classroom technology and AI","geography":"Utah, United States","publishedAt":"2026-10-05","publicationDate":"2026-10-05","eventDate":null,"sourceName":"Utah Public Notice Website (USBE October 2026 committee materials)","sourceLabel":"Draft state board rule","sourceUrl":"https://www.utah.gov/pmn/files/1497251.pdf","evidenceClass":"standards-guidance","outcomeClass":"emerging","topics":["governance-procurement","data-security","accessibility-workforce"],"finding":"Draft 1 of R277-334, Classroom Technology and Artificial Intelligence Governance, dated October 5, 2026, implements H.B. 273 (2026). LEAs must adopt the Board's model AI use policy or a compliant local policy before July 1, 2027, keep an inventory of approved student-facing AI tools, ban biometric surveillance and psychological profiling, and prohibit student generative AI for academic work unless an educator authorises it for a specific purpose. Educators may not use generative AI to independently grade work or make high-stakes determinations. Parents get written notice with a metadata-dictionary link when generative AI is used. High-risk AI interactions may not be used with students. LEAs must train staff, keep records and certify compliance to receive certain state technology funds.","sledRelevance":"A new state rule draft turns AI policy into auditable operating duties for every Utah LEA, as Utah districts diverge on student Gemini access. Several duties, such as tool inventories, parent notice, educator authorisation and training records, mirror requirements already in the archive for Florida, Oklahoma and Maryland.","evidence":"Primary-source draft rule text with tracked changes, plus the Board memo and draft model policy posted for the October 2026 committee meeting. It is a proposal at first reading; it reports no outcomes.","architectureImplications":"Interpretation: districts need a maintained registry of approved student-facing AI tools linked to the metadata dictionary, device filtering by grade band, and a parent-accessible monitoring system referenced in the rule.","governanceImplications":"Policy adoption needs a public meeting, submission to the Superintendent and review at least every two years; non-compliance can bring corrective action or withheld funds.","securityPrivacyImplications":"Explicit bans on biometric surveillance and psychological profiling; AI tools must comply with Utah student privacy law and LEA data governance.","caveats":"Draft at first reading; text may change before final adoption. The draft defines 'high-stakes artificial intelligence interaction' but its prohibition refers to 'high-risk', a drafting inconsistency to watch. No fiscal or workload estimate in the materials opened.","streamIds":["k12"],"roles":{"sales":"Frame this as a compliance calendar. Utah's draft rule gives every LEA until July 1, 2027 to adopt an AI policy, maintain an approved student-facing AI tool inventory, train staff, notify parents and certify compliance to keep certain state technology funds. That supports a bounded readiness engagement: inventory, policy gap review and training records. The draft is not final, and it gives no evidence that compliance improves learning or safety.","engineering":"The rule makes the AI tool inventory a system of record. Each approved student-facing tool needs a link to the metadata dictionary, grade-band filtering and evidence of instructional value, and generative AI use must trigger written parent notice. Check whether tools can be limited to educator-authorised use, whether logs exist for compliance reviews, and whether any feature could count as biometric surveillance, psychological profiling or a high-risk interaction, which the draft bans.","delivery":"Deliver a compliance workplan: adopt the model AI policy or a local version after a public meeting, build and maintain the approved-tool inventory, set up parent notification, train staff before rollout, and keep training and monitoring records. Curriculum owns educator authorisation norms; IT owns the inventory and filtering; the policy office owns submission and biennial review. Track the final rule text, since the draft may change."},"roleDetails":{"sales":{"customerProblem":"Utah LEAs face new statewide AI and classroom technology duties with a July 1, 2027 deadline and funding conditions.","stakeholders":["superintendent","LEA board","technology director","teaching and learning director","student data privacy manager","charter school leaders"],"discoveryQuestions":["Do you have an inventory of approved student-facing AI tools?","How will teachers record when they authorise student AI use?","Can you produce training records for every educator?","Which tools might involve biometric or profiling features?"],"valueHypothesis":"Early inventory and policy work reduces the risk of non-compliance findings and withheld technology funds once the rule is final.","potentialEngagement":"Six-to-eight-week R277-334 readiness review: tool inventory, policy gap analysis, parent notification templates and training plan.","unsupportedClaims":["That the draft will be adopted unchanged","That compliance improves student outcomes","Any specific cost of compliance"]},"engineering":{"fit":"Directly relevant to Utah districts and charters; a template for other states with similar rules.","architectureIntegration":"Approved-tool registry tied to the student data metadata dictionary, filtering by grade band, and parent-facing tool lists and monitoring access.","prerequisites":["current edtech and AI tool inventory","metadata dictionary under Utah privacy law","filtering and device management by grade"],"constraints":["draft text may change","applies to Utah LEAs","grade-level device and screen-time limits affect where AI tools can run"],"security":"Exclude tools with biometric surveillance or psychological profiling; confirm vendor compliance with Utah student privacy law before adding a tool to the inventory.","proofOfValue":["Produce the approved-tool inventory with metadata links for a sample school","Demonstrate parent notice for one generative AI activity","Show training completion records for one staff group"]},"delivery":{"work":"Implement R277-334 duties: policy adoption, approved AI tool inventory, educator authorisation practice, parent notice, training and compliance records.","dependencies":["final rule adoption","USBE model policy","vendor privacy agreements"],"ownership":"Policy office owns adoption and submission; IT owns inventory and filtering; teaching and learning owns educator authorisation and training.","skillsAdoption":"Educators need training on approved tools, assignment-level AI expectations and not using generative AI to grade independently.","governanceCheckpoints":["public meeting before policy adoption","submission to the Superintendent","biennial policy review"],"acceptanceCriteria":["Proposed: 100% of student-facing AI tools in the inventory with privacy review","Proposed: training records for all educators before rollout","Proposed: parent notice issued for each generative AI use"],"risks":["rule text changes late","inventory goes stale","funding withheld for non-compliance"]}},"retrievedAt":"2026-10-07T22:06:38-05:00","enrichedAt":"2026-10-07T22:06:38-05:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Mandatory staff training on AI tools and integrity; LEAs must plan for students with technology-related learning difficulties and keep IEP and 504 exemptions.","procurementImplications":"Vendors must fit the approved-tool inventory, privacy law and metadata dictionary, and avoid biometric or profiling features to be usable with students.","operatingModelImplications":"AI governance becomes a recurring compliance function with records, reporting and funding consequences.","sourceVerification":{"openedUrl":"https://www.utah.gov/pmn/files/1497251.pdf","referenceExcerpt":"High-risk artificial intelligence interaction may not be used with students.","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}